Course-Correct to DeFi Lacking Default Deficiency

Abstract

This paper explores methods of assessing risk on-chain by efficiently integrating off-chain identity- and attribute-verification and on-chain transaction activity. While decentralized finance (DeFi) is a well-suited application of permissionless blockchains, it is severely constrained in its ability to reconcile real-world identities and, as a result, to quantify their associated transaction risk using solely on-chain data, limiting its realistic applications. Opening the ecosystem to a broader range of use cases requires consistent pseudonymity and quantifiable reputation. Traditional finance quantifies risk by collecting and vetting reputation information for an individual, such as credit scores or payment history. We explore a mechanism to incorporate these traditional trust factors into the DeFi ecosystem while both preserving individual privacy within a competitive and fair environment and retaining compatibility with existing platforms such as Ethereum. Even though blockchains are inherently public, our solution gives users control over the release of information that pertains to them. Consequently, our contribution focuses on customized methods that balance the level of disclosure of verfiable, provably-sourced user information against the likelihood of the user successfully gaining access to a desired resource, such as a loan under mutually-agreeable terms. Our solution is consistent with the zero-trust model in that it imports explicit trust from recognized sources through relevant, continuously updated metrics.